Pandas Profiling Report

Dataset statistics

Number of variables	15
Number of observations	1143
Missing cells	764
Missing cells (%)	4.5%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	134.1 KiB
Average record size in memory	120.1 B

Variable types

Numeric	10
Categorical	5

Warnings

`ad_id` is highly correlated with `campaign_id` and 1 other fields	High correlation
`campaign_id` is highly correlated with `ad_id` and 4 other fields	High correlation
`fb_campaign_id` is highly correlated with `ad_id` and 1 other fields	High correlation
`interest1` is highly correlated with `interest2` and 1 other fields	High correlation
`interest2` is highly correlated with `interest1` and 1 other fields	High correlation
`interest3` is highly correlated with `interest1` and 1 other fields	High correlation
`impressions` is highly correlated with `campaign_id` and 4 other fields	High correlation
`clicks` is highly correlated with `campaign_id` and 4 other fields	High correlation
`spent` is highly correlated with `campaign_id` and 4 other fields	High correlation
`total_conversion` is highly correlated with `impressions` and 3 other fields	High correlation
`approved_conversion` is highly correlated with `impressions` and 3 other fields	High correlation
`ad_id` is highly correlated with `campaign_id` and 5 other fields	High correlation
`campaign_id` is highly correlated with `ad_id` and 5 other fields	High correlation
`fb_campaign_id` is highly correlated with `ad_id` and 3 other fields	High correlation
`interest1` is highly correlated with `interest2` and 1 other fields	High correlation
`interest2` is highly correlated with `interest1` and 1 other fields	High correlation
`interest3` is highly correlated with `interest1` and 1 other fields	High correlation
`impressions` is highly correlated with `ad_id` and 5 other fields	High correlation
`clicks` is highly correlated with `ad_id` and 4 other fields	High correlation
`spent` is highly correlated with `ad_id` and 5 other fields	High correlation
`total_conversion` is highly correlated with `ad_id` and 5 other fields	High correlation
`approved_conversion` is highly correlated with `total_conversion`	High correlation
`ad_id` is highly correlated with `campaign_id` and 1 other fields	High correlation
`campaign_id` is highly correlated with `ad_id` and 4 other fields	High correlation
`fb_campaign_id` is highly correlated with `ad_id` and 1 other fields	High correlation
`interest1` is highly correlated with `interest2` and 1 other fields	High correlation
`interest2` is highly correlated with `interest1` and 1 other fields	High correlation
`interest3` is highly correlated with `interest1` and 1 other fields	High correlation
`impressions` is highly correlated with `campaign_id` and 3 other fields	High correlation
`clicks` is highly correlated with `campaign_id` and 3 other fields	High correlation
`spent` is highly correlated with `campaign_id` and 3 other fields	High correlation
`total_conversion` is highly correlated with `impressions` and 3 other fields	High correlation
`approved_conversion` is highly correlated with `total_conversion`	High correlation
`fb_campaign_id` is highly correlated with `gender` and 4 other fields	High correlation
`interest2` is highly correlated with `interest3` and 2 other fields	High correlation
`gender` is highly correlated with `fb_campaign_id`	High correlation
`interest3` is highly correlated with `interest2` and 2 other fields	High correlation
`impressions` is highly correlated with `total_conversion` and 3 other fields	High correlation
`total_conversion` is highly correlated with `impressions` and 3 other fields	High correlation
`approved_conversion` is highly correlated with `impressions` and 3 other fields	High correlation
`spent` is highly correlated with `impressions` and 3 other fields	High correlation
`clicks` is highly correlated with `impressions` and 3 other fields	High correlation
`campaign_id` is highly correlated with `fb_campaign_id` and 3 other fields	High correlation
`reporting_start` is highly correlated with `fb_campaign_id` and 2 other fields	High correlation
`interest1` is highly correlated with `interest2` and 2 other fields	High correlation
`reporting_end` is highly correlated with `fb_campaign_id` and 2 other fields	High correlation
`ad_id` is highly correlated with `fb_campaign_id` and 4 other fields	High correlation
`campaign_id` is highly correlated with `gender`	High correlation
`reporting_start` is highly correlated with `reporting_end`	High correlation
`gender` is highly correlated with `campaign_id`	High correlation
`reporting_end` is highly correlated with `reporting_start`	High correlation
`campaign_id` has 382 (33.4%) missing values	Missing
`fb_campaign_id` has 382 (33.4%) missing values	Missing
`ad_id` has unique values	Unique
`clicks` has 207 (18.1%) zeros	Zeros
`spent` has 207 (18.1%) zeros	Zeros
`approved_conversion` has 559 (48.9%) zeros	Zeros

Reproduction

Analysis started	2021-08-01 14:12:27.941409
Analysis finished	2021-08-01 14:12:47.455685
Duration	19.51 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

ad_id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	1143
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	987261.1304

Minimum	708746
Maximum	1314415
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	708746
5-th percentile	734245.3
Q1	777632.5
median	1121185
Q3	1121804.5
95-th percentile	1314348.9
Maximum	1314415
Range	605669
Interquartile range (IQR)	344172

Descriptive statistics

Standard deviation	193992.8147
Coefficient of variation (CV)	0.196495951
Kurtosis	-1.412358983
Mean	987261.1304
Median Absolute Deviation (MAD)	169983
Skewness	-0.1027848097
Sum	1128439472
Variance	3.763321217 × 10¹⁰
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1122303	1	0.1%
1121141	1	0.1%
1121131	1	0.1%
1121132	1	0.1%
1121133	1	0.1%
1121134	1	0.1%
1121136	1	0.1%
1121138	1	0.1%
1121142	1	0.1%
1121129	1	0.1%
Other values (1133)	1133	99.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
708746	1	0.1%
708749	1	0.1%
708771	1	0.1%
708815	1	0.1%
708818	1	0.1%
708820	1	0.1%
708889	1	0.1%
708895	1	0.1%
708953	1	0.1%
708958	1	0.1%

Value	Count	Frequency (%)
1314415	1	0.1%
1314414	1	0.1%
1314412	1	0.1%
1314411	1	0.1%
1314410	1	0.1%
1314409	1	0.1%
1314408	1	0.1%
1314407	1	0.1%
1314406	1	0.1%
1314405	1	0.1%

reporting_start
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	14
Distinct (%)	1.2%
Missing	0
Missing (%)	0.0%
Memory size	9.1 KiB

23-08-2017	109
18-08-2017	109
19-08-2017	105
21-08-2017	102
22-08-2017	96
Other values (9)	622

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	11430
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	17-08-2017
2nd row	17-08-2017
3rd row	17-08-2017
4th row	30-08-2017
5th row	17-08-2017

Common Values

Value	Count	Frequency (%)
23-08-2017	109	9.5%
18-08-2017	109	9.5%
19-08-2017	105	9.2%
21-08-2017	102	8.9%
22-08-2017	96	8.4%
20-08-2017	93	8.1%
24-08-2017	74	6.5%
29-08-2017	70	6.1%
28-08-2017	69	6.0%
26-08-2017	68	5.9%
Other values (4)	248	21.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
23-08-2017	109	9.5%
18-08-2017	109	9.5%
19-08-2017	105	9.2%
21-08-2017	102	8.9%
22-08-2017	96	8.4%
20-08-2017	93	8.1%
24-08-2017	74	6.5%
29-08-2017	70	6.1%
28-08-2017	69	6.0%
26-08-2017	68	5.9%
Other values (4)	248	21.7%

Most occurring characters

Value	Count	Frequency (%)
0	2445	21.4%
-	2286	20.0%
2	2048	17.9%
1	1513	13.2%
8	1321	11.6%
7	1261	11.0%
3	175	1.5%
9	175	1.5%
4	74	0.6%
6	68	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9144	80.0%
Dash Punctuation	2286	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2445	26.7%
2	2048	22.4%
1	1513	16.5%
8	1321	14.4%
7	1261	13.8%
3	175	1.9%
9	175	1.9%
4	74	0.8%
6	68	0.7%
5	64	0.7%

Dash Punctuation

Value	Count	Frequency (%)
-	2286	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11430	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	2445	21.4%
-	2286	20.0%
2	2048	17.9%
1	1513	13.2%
8	1321	11.6%
7	1261	11.0%
3	175	1.5%
9	175	1.5%
4	74	0.6%
6	68	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11430	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	2445	21.4%
-	2286	20.0%
2	2048	17.9%
1	1513	13.2%
8	1321	11.6%
7	1261	11.0%
3	175	1.5%
9	175	1.5%
4	74	0.6%
6	68	0.6%

reporting_end
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	14
Distinct (%)	1.2%
Missing	0
Missing (%)	0.0%
Memory size	9.1 KiB

23-08-2017	109
18-08-2017	109
19-08-2017	105
21-08-2017	102
22-08-2017	96
Other values (9)	622

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	11430
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	17-08-2017
2nd row	17-08-2017
3rd row	17-08-2017
4th row	30-08-2017
5th row	17-08-2017

Common Values

Value	Count	Frequency (%)
23-08-2017	109	9.5%
18-08-2017	109	9.5%
19-08-2017	105	9.2%
21-08-2017	102	8.9%
22-08-2017	96	8.4%
20-08-2017	93	8.1%
24-08-2017	74	6.5%
29-08-2017	70	6.1%
28-08-2017	69	6.0%
26-08-2017	68	5.9%
Other values (4)	248	21.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
23-08-2017	109	9.5%
18-08-2017	109	9.5%
19-08-2017	105	9.2%
21-08-2017	102	8.9%
22-08-2017	96	8.4%
20-08-2017	93	8.1%
24-08-2017	74	6.5%
29-08-2017	70	6.1%
28-08-2017	69	6.0%
26-08-2017	68	5.9%
Other values (4)	248	21.7%

Most occurring characters

Value	Count	Frequency (%)
0	2445	21.4%
-	2286	20.0%
2	2048	17.9%
1	1513	13.2%
8	1321	11.6%
7	1261	11.0%
3	175	1.5%
9	175	1.5%
4	74	0.6%
6	68	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	9144	80.0%
Dash Punctuation	2286	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2445	26.7%
2	2048	22.4%
1	1513	16.5%
8	1321	14.4%
7	1261	13.8%
3	175	1.9%
9	175	1.9%
4	74	0.8%
6	68	0.7%
5	64	0.7%

Dash Punctuation

Value	Count	Frequency (%)
-	2286	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11430	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	2445	21.4%
-	2286	20.0%
2	2048	17.9%
1	1513	13.2%
8	1321	11.6%
7	1261	11.0%
3	175	1.5%
9	175	1.5%
4	74	0.6%
6	68	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11430	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	2445	21.4%
-	2286	20.0%
2	2048	17.9%
1	1513	13.2%
8	1321	11.6%
7	1261	11.0%
3	175	1.5%
9	175	1.5%
4	74	0.6%
6	68	0.6%

campaign_id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	0.4%
Missing	382
Missing (%)	33.4%
Memory size	9.1 KiB

936.0	464
1178.0	243
916.0	54

Length

Max length	6
Median length	5
Mean length	5.319316689
Min length	5

Characters and Unicode

Total characters	4048
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	916.0
2nd row	916.0
3rd row	916.0
4th row	916.0
5th row	916.0

Common Values

Value	Count	Frequency (%)
936.0	464	40.6%
1178.0	243	21.3%
916.0	54	4.7%
(Missing)	382	33.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
936.0	464	61.0%
1178.0	243	31.9%
916.0	54	7.1%

Most occurring characters

Value	Count	Frequency (%)
.	761	18.8%
0	761	18.8%
1	540	13.3%
9	518	12.8%
6	518	12.8%
3	464	11.5%
7	243	6.0%
8	243	6.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3287	81.2%
Other Punctuation	761	18.8%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	761	23.2%
1	540	16.4%
9	518	15.8%
6	518	15.8%
3	464	14.1%
7	243	7.4%
8	243	7.4%

Other Punctuation

Value	Count	Frequency (%)
.	761	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	4048	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	761	18.8%
0	761	18.8%
1	540	13.3%
9	518	12.8%
6	518	12.8%
3	464	11.5%
7	243	6.0%
8	243	6.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4048	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	761	18.8%
0	761	18.8%
1	540	13.3%
9	518	12.8%
6	518	12.8%
3	464	11.5%
7	243	6.0%
8	243	6.0%

fb_campaign_id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	488
Distinct (%)	64.1%
Missing	382
Missing (%)	33.4%
Infinite	0
Infinite (%)	0.0%
Mean	123915.0604

Minimum	103916
Maximum	144622
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	103916
5-th percentile	104228
Q1	110982
median	116341
Q3	144549
95-th percentile	144604
Maximum	144622
Range	40706
Interquartile range (IQR)	33567

Descriptive statistics

Standard deviation	14933.70416
Coefficient of variation (CV)	0.1205156509
Kurtosis	-1.419972402
Mean	123915.0604
Median Absolute Deviation (MAD)	7330
Skewness	0.4662547238
Sum	94299361
Variance	223015520
Monotonicity	Increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
144536	6	0.5%
144611	6	0.5%
144562	6	0.5%
144599	6	0.5%
144597	5	0.4%
144537	5	0.4%
144549	5	0.4%
144565	5	0.4%
144554	5	0.4%
144572	5	0.4%
Other values (478)	707	61.9%
(Missing)	382	33.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
103916	1	0.1%
103917	1	0.1%
103920	1	0.1%
103928	2	0.2%
103929	1	0.1%
103940	1	0.1%
103941	1	0.1%
103951	1	0.1%
103952	1	0.1%
103955	1	0.1%

Value	Count	Frequency (%)
144622	4	0.3%
144621	2	0.2%
144620	1	0.1%
144619	3	0.3%
144618	1	0.1%
144617	2	0.2%
144616	2	0.2%
144615	2	0.2%
144614	3	0.3%
144613	1	0.1%

age
Categorical

Distinct	4
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	9.1 KiB

30-34	426
45-49	259
35-39	248
40-44	210

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	5715
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	30-34
2nd row	30-34
3rd row	30-34
4th row	30-34
5th row	30-34

Common Values

Value	Count	Frequency (%)
30-34	426	37.3%
45-49	259	22.7%
35-39	248	21.7%
40-44	210	18.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
30-34	426	37.3%
45-49	259	22.7%
35-39	248	21.7%
40-44	210	18.4%

Most occurring characters

Value	Count	Frequency (%)
4	1574	27.5%
3	1348	23.6%
-	1143	20.0%
0	636	11.1%
5	507	8.9%
9	507	8.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4572	80.0%
Dash Punctuation	1143	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
4	1574	34.4%
3	1348	29.5%
0	636	13.9%
5	507	11.1%
9	507	11.1%

Dash Punctuation

Value	Count	Frequency (%)
-	1143	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	5715	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
4	1574	27.5%
3	1348	23.6%
-	1143	20.0%
0	636	11.1%
5	507	8.9%
9	507	8.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5715	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
4	1574	27.5%
3	1348	23.6%
-	1143	20.0%
0	636	11.1%
5	507	8.9%
9	507	8.9%

gender
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	9.1 KiB

M	592
F	551

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1143
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	M
2nd row	M
3rd row	M
4th row	M
5th row	M

Common Values

Value	Count	Frequency (%)
M	592	51.8%
F	551	48.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
m	592	51.8%
f	551	48.2%

Most occurring characters

Value	Count	Frequency (%)
M	592	51.8%
F	551	48.2%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1143	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
M	592	51.8%
F	551	48.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1143	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
M	592	51.8%
F	551	48.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1143	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
M	592	51.8%
F	551	48.2%

interest1
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	40
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	32.7664042

Minimum	2
Maximum	114
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	2
5-th percentile	10
Q1	16
median	25
Q3	31
95-th percentile	105.9
Maximum	114
Range	112
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	26.95213098
Coefficient of variation (CV)	0.8225538211
Kurtosis	2.226426216
Mean	32.7664042
Median Absolute Deviation (MAD)	7
Skewness	1.766272906
Sum	37452
Variance	726.4173642
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=40)

Value	Count	Frequency (%)
16	140	12.2%
10	85	7.4%
29	77	6.7%
27	60	5.2%
15	51	4.5%
28	51	4.5%
20	49	4.3%
64	48	4.2%
63	46	4.0%
18	43	3.8%
Other values (30)	493	43.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	25	2.2%
7	24	2.1%
10	85	7.4%
15	51	4.5%
16	140	12.2%
18	43	3.8%
19	32	2.8%
20	49	4.3%
21	36	3.1%
22	33	2.9%

Value	Count	Frequency (%)
114	5	0.4%
113	6	0.5%
112	7	0.6%
111	6	0.5%
110	8	0.7%
109	6	0.5%
108	7	0.6%
107	8	0.7%
106	5	0.4%
105	7	0.6%

interest2
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	66
Distinct (%)	5.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	36.24584427

Minimum	3
Maximum	118
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	3
5-th percentile	12
Q1	20
median	28
Q3	35
95-th percentile	109
Maximum	118
Range	115
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	26.93785281
Coefficient of variation (CV)	0.7431983818
Kurtosis	2.183842555
Mean	36.24584427
Median Absolute Deviation (MAD)	7
Skewness	1.749598895
Sum	41429
Variance	725.647914
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
32	53	4.6%
21	50	4.4%
31	49	4.3%
22	44	3.8%
30	43	3.8%
33	41	3.6%
24	40	3.5%
17	39	3.4%
19	39	3.4%
29	39	3.4%
Other values (56)	706	61.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3	2	0.2%
4	7	0.6%
5	3	0.3%
6	5	0.4%
7	3	0.3%
8	8	0.7%
9	7	0.6%
10	8	0.7%
11	12	1.0%
12	13	1.1%

Value	Count	Frequency (%)
118	1	0.1%
117	4	0.3%
116	8	0.7%
115	5	0.4%
114	8	0.7%
113	10	0.9%
112	6	0.5%
111	7	0.6%
110	5	0.4%
109	5	0.4%

interest3
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	69
Distinct (%)	6.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	36.22222222

Minimum	3
Maximum	120
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	3
5-th percentile	12
Q1	20
median	28
Q3	35
95-th percentile	108
Maximum	120
Range	117
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	26.92467855
Coefficient of variation (CV)	0.7433193464
Kurtosis	2.19218859
Mean	36.22222222
Median Absolute Deviation (MAD)	7
Skewness	1.753171733
Sum	41402
Variance	724.9383148
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22	51	4.5%
32	50	4.4%
21	45	3.9%
30	45	3.9%
20	44	3.8%
31	42	3.7%
24	41	3.6%
33	41	3.6%
25	39	3.4%
29	39	3.4%
Other values (59)	706	61.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3	4	0.3%
4	3	0.3%
5	3	0.3%
6	3	0.3%
7	9	0.8%
8	7	0.6%
9	5	0.4%
10	4	0.3%
11	17	1.5%
12	13	1.1%

Value	Count	Frequency (%)
120	1	0.1%
119	1	0.1%
118	3	0.3%
117	2	0.2%
116	6	0.5%
115	6	0.5%
114	7	0.6%
113	5	0.4%
112	9	0.8%
111	10	0.9%

impressions
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1130
Distinct (%)	98.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	186732.133

Minimum	87
Maximum	3052003
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	87
5-th percentile	741.2
Q1	6503.5
median	51509
Q3	221769
95-th percentile	894449.4
Maximum	3052003
Range	3051916
Interquartile range (IQR)	215265.5

Descriptive statistics

Standard deviation	312762.1832
Coefficient of variation (CV)	1.674924279
Kurtosis	13.12408972
Mean	186732.133
Median Absolute Deviation (MAD)	49955
Skewness	3.010185014
Sum	213434828
Variance	9.782018325 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3812	2	0.2%
529	2	0.2%
2479	2	0.2%
1539	2	0.2%
2879	2	0.2%
2755	2	0.2%
1030	2	0.2%
2077	2	0.2%
11199	2	0.2%
4259	2	0.2%
Other values (1120)	1123	98.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
87	1	0.1%
152	2	0.2%
199	1	0.1%
219	1	0.1%
239	1	0.1%
246	1	0.1%
255	1	0.1%
259	1	0.1%
292	1	0.1%
343	1	0.1%

Value	Count	Frequency (%)
3052003	1	0.1%
2286228	1	0.1%
2223278	1	0.1%
2080666	1	0.1%
1705246	1	0.1%
1663441	1	0.1%
1447755	1	0.1%
1428421	1	0.1%
1392288	1	0.1%
1391924	1	0.1%

clicks
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	183
Distinct (%)	16.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	33.39020122

Minimum	0
Maximum	421
Zeros	207
Zeros (%)	18.1%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	8
Q3	37.5
95-th percentile	161.9
Maximum	421
Range	421
Interquartile range (IQR)	36.5

Descriptive statistics

Standard deviation	56.8924383
Coefficient of variation (CV)	1.703866291
Kurtosis	8.539645174
Mean	33.39020122
Median Absolute Deviation (MAD)	8
Skewness	2.71218742
Sum	38165
Variance	3236.749536
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	207	18.1%
1	119	10.4%
2	70	6.1%
3	51	4.5%
4	34	3.0%
5	34	3.0%
7	29	2.5%
6	18	1.6%
9	17	1.5%
20	16	1.4%
Other values (173)	548	47.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	207	18.1%
1	119	10.4%
2	70	6.1%
3	51	4.5%
4	34	3.0%
5	34	3.0%
6	18	1.6%
7	29	2.5%
8	14	1.2%
9	17	1.5%

Value	Count	Frequency (%)
421	1	0.1%
367	1	0.1%
353	1	0.1%
346	1	0.1%
340	1	0.1%
295	1	0.1%
282	1	0.1%
276	1	0.1%
272	1	0.1%
268	1	0.1%

spent
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	869
Distinct (%)	76.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	51.36065613

Minimum	0
Maximum	639.9499981
Zeros	207
Zeros (%)	18.1%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1.480000019
median	12.36999989
Q3	60.02499992
95-th percentile	248.5080003
Maximum	639.9499981
Range	639.9499981
Interquartile range (IQR)	58.5449999

Descriptive statistics

Standard deviation	86.90841794
Coefficient of variation (CV)	1.692120477
Kurtosis	8.843981056
Mean	51.36065613
Median Absolute Deviation (MAD)	12.36999989
Skewness	2.70886702
Sum	58705.22996
Variance	7553.073108
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	207	18.1%
1.379999995	5	0.4%
1.289999962	4	0.3%
1.539999962	4	0.3%
1.230000019	3	0.3%
1.320000052	3	0.3%
1.580000043	3	0.3%
1.590000033	3	0.3%
1.570000052	3	0.3%
1.370000005	3	0.3%
Other values (859)	905	79.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	207	18.1%
0.180000007	1	0.1%
0.239999995	1	0.1%
0.409999996	1	0.1%
0.49000001	1	0.1%
0.529999971	1	0.1%
0.540000021	1	0.1%
0.569999993	2	0.2%
0.600000024	1	0.1%
0.720000029	1	0.1%

Value	Count	Frequency (%)
639.9499981	1	0.1%
612.3000032	1	0.1%
603.380002	1	0.1%
541.7000023	1	0.1%
465.0799981	1	0.1%
429.4799981	1	0.1%
422.8400038	1	0.1%
420.5799983	1	0.1%
409.5600026	1	0.1%
402.3000026	1	0.1%

total_conversion
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	32
Distinct (%)	2.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.855643045

Minimum	0
Maximum	60
Zeros	8
Zeros (%)	0.7%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	1
Q3	3
95-th percentile	11
Maximum	60
Range	60
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	4.483593472
Coefficient of variation (CV)	1.570081905
Kurtosis	38.58919567
Mean	2.855643045
Median Absolute Deviation (MAD)	0
Skewness	5.095918881
Sum	3264
Variance	20.10261042
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
1	666	58.3%
2	162	14.2%
3	78	6.8%
4	61	5.3%
5	41	3.6%
6	22	1.9%
7	16	1.4%
11	13	1.1%
8	13	1.1%
13	9	0.8%
Other values (22)	62	5.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8	0.7%
1	666	58.3%
2	162	14.2%
3	78	6.8%
4	61	5.3%
5	41	3.6%
6	22	1.9%
7	16	1.4%
8	13	1.1%
9	7	0.6%

Value	Count	Frequency (%)
60	1	0.1%
40	1	0.1%
38	1	0.1%
31	2	0.2%
30	1	0.1%
28	1	0.1%
26	2	0.2%
24	1	0.1%
23	3	0.3%
22	4	0.3%

approved_conversion
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	16
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.9440069991

Minimum	0
Maximum	21
Zeros	559
Zeros (%)	48.9%
Negative	0
Negative (%)	0.0%
Memory size	9.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	1
95-th percentile	4
Maximum	21
Range	21
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.737708006
Coefficient of variation (CV)	1.840778731
Kurtosis	34.59340334
Mean	0.9440069991
Median Absolute Deviation (MAD)	1
Skewness	4.837539423
Sum	1079
Variance	3.019629114
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=16)

Value	Count	Frequency (%)
0	559	48.9%
1	403	35.3%
2	86	7.5%
3	35	3.1%
4	24	2.1%
6	7	0.6%
5	7	0.6%
8	5	0.4%
10	4	0.3%
7	4	0.3%
Other values (6)	9	0.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	559	48.9%
1	403	35.3%
2	86	7.5%
3	35	3.1%
4	24	2.1%
5	7	0.6%
6	7	0.6%
7	4	0.3%
8	5	0.4%
9	3	0.3%

Value	Count	Frequency (%)
21	1	0.1%
17	1	0.1%
14	2	0.2%
13	1	0.1%
12	1	0.1%
10	4	0.3%
9	3	0.3%
8	5	0.4%
7	4	0.3%
6	7	0.6%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	ad_id	reporting_start	reporting_end	campaign_id	fb_campaign_id	age	gender	interest1	interest2	interest3	impressions	clicks	spent	total_conversion	approved_conversion
0	708746	17-08-2017	17-08-2017	916.0	103916.0	30-34	M	15	17	17	7350	1	1.43	2	1
1	708749	17-08-2017	17-08-2017	916.0	103917.0	30-34	M	16	19	21	17861	2	1.82	2	0
2	708771	17-08-2017	17-08-2017	916.0	103920.0	30-34	M	20	25	22	693	0	0.00	1	0
3	708815	30-08-2017	30-08-2017	916.0	103928.0	30-34	M	28	32	32	4259	1	1.25	1	0
4	708818	17-08-2017	17-08-2017	916.0	103928.0	30-34	M	28	33	32	4133	1	1.29	1	1
5	708820	17-08-2017	17-08-2017	916.0	103929.0	30-34	M	29	30	30	1915	0	0.00	1	1
6	708889	17-08-2017	17-08-2017	916.0	103940.0	30-34	M	15	16	17	15615	3	4.77	1	0
7	708895	17-08-2017	17-08-2017	916.0	103941.0	30-34	M	16	20	18	10951	1	1.27	1	1
8	708953	17-08-2017	17-08-2017	916.0	103951.0	30-34	M	27	31	31	2355	1	1.50	1	0
9	708958	30-08-2017	30-08-2017	916.0	103952.0	30-34	M	28	32	31	9502	3	3.16	1	0

Last rows

	ad_id	reporting_start	reporting_end	campaign_id	fb_campaign_id	age	gender	interest1	interest2	interest3	impressions	clicks	spent	total_conversion	approved_conversion
1133	1314405	19-08-2017	19-08-2017	NaN	NaN	45-49	F	104	107	110	558666	110	162.639998	14	5
1134	1314406	19-08-2017	19-08-2017	NaN	NaN	45-49	F	105	106	109	1118200	235	333.749994	11	4
1135	1314407	19-08-2017	19-08-2017	NaN	NaN	45-49	F	106	112	108	107100	23	33.710001	1	0
1136	1314408	19-08-2017	19-08-2017	NaN	NaN	45-49	F	107	113	112	877769	160	232.590001	13	4
1137	1314409	19-08-2017	19-08-2017	NaN	NaN	45-49	F	108	112	112	212508	33	47.690000	4	1
1138	1314410	19-08-2017	19-08-2017	NaN	NaN	45-49	F	109	111	114	1129773	252	358.189997	13	2
1139	1314411	19-08-2017	19-08-2017	NaN	NaN	45-49	F	110	111	116	637549	120	173.880003	3	0
1140	1314412	19-08-2017	19-08-2017	NaN	NaN	45-49	F	111	113	117	151531	28	40.289999	2	0
1141	1314414	17-08-2017	17-08-2017	NaN	NaN	45-49	F	113	114	117	790253	135	198.710000	8	2
1142	1314415	17-08-2017	17-08-2017	NaN	NaN	45-49	F	114	116	118	513161	114	165.609999	5	2

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Dash Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Dash Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Dash Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows